GEMAS: Phosphorus in European agricultural soil - sources versus sinks at the continental-scale - the geological perspective.

Phosphorus (P) is one of the essential elements for life on Earth. As a major nutrient it is needed for healthy growth both in plants and living organisms. Although the abundance of P in the Earth's upper continental crust is relatively high (655 mg/kg), many soil types are poor in available phosphorus. The main natural factors controlling the availability of P in soil are pH, mineralogy, and formation of insoluble complexes with Al and Fe under acidic, and with Ca and Mg under alkaline soil conditions. Superimposed weathering processes and climate contribute strongly to P mobility and availability. Additionally, a large fraction of total soil P is in organic forms, which are not directly available to plants. Phosphorus is a major component in fertilisers and thus a significant source of anthropogenic P in soil and water. In the agricultural soil samples that were collected during the Geochemical Mapping of Agricultural and grazing land Soil (GEMAS) project, the total P concentrations (XRF, median 786 m/kg) are only slightly higher than those extracted by hot aqua regia (AR, median 653 mg/kg), while the median concentration in the weak MMI® cold extraction is as low as 4.1 mg/kg. The AR results show very low P concentrations over the coarse-grained sandy sediments of the last glaciation in central and northern Europe and in calcareous soil. The southern limit of the last glaciation is visible as a concentration break on the geochemical maps. In general, north-eastern and north-western Europe are marked by high P values, probably related to cold and humid climate and enrichment in humus-rich coastal soil. The spatial distribution of P at the continental-scale is dominated by geogenic and climatic factors, and the anthropogenic influence is difficult to assess and quantify.

Excess Cr and Ni in top soil: Comparing the effect of geology, diffuse contamination, and biogenic influence.

Chromium (Cr) and nickel (Ni) are among the elements that are most mined, processed and used in modern industry and society. A realistic estimate of the diffuse contamination that has left a footprint on soil during the last 200 years by worldwide industrialization requires recognition and assessment of the dominant natural and anthropogenic sources. The relations between geogenic, anthropogenic, and biogenic Cr and Ni sources are estimated from eight large-scale geochemical surveys, by comparing the cumulative distribution functions (CDF) of the elements in top- and sub soil using cumulative probability (CP) diagrams. This method makes it possible to estimate the effect of long-term diffuse contamination on soil without monitoring. The method offers a cheaper and more reliable method for estimating diffuse contamination at the continental to regional scale than classical monitoring methods. The impact of diffuse contamination can be recognized at the low-concentration end while strong local contamination is shown as a distort at the high-concentration end of the distribution. Chromium, due to its structural similarities with essential nutrients, shows a clear biological signal in the CP-diagram. The bio-adjustment of Cr and Ni limits the accuracy of the diffuse contamination estimates. Combining CDF analysis with spatial mapping provides insight into the dominant contamination processes that distort the top soil CDF relative to the sub soil CDF. For both elements, a diffuse contamination signal of <1 mg/kg is obtained for soils at the European scale. Agricultural soil is affected by contamination from farming practices and shows higher excess Cr and Ni in top soil than forest soil. Although the world has faced several centuries of industrial development and Cr and Ni are used "everywhere", this is not reflected in surface soil at the continental to regional scale. The regional distribution of both elements is dominated by natural sources and processes.

Quantifying diffuse contamination: Comparing silver and mercury in organogenic and minerogenic soil.

For both, silver (Ag) and mercury (Hg), the median concentrations in an aqua regia extraction of minerogenic top- and subsoil from continental scale geochemical surveys (Australia, China, Europe) are around 0.02 mg/kg. When the soil O horizon is collected as topsoil sample, the concentration of again both elements is higher by about a factor of 10 (range 7-30), with median concentrations around 0.2 mg/kg Ag and Hg. Geochemical maps of top- and subsoil at different scales for both elements display regional patterns which reflect mainly geology, climate and topography. Anthropogenic sources like mines, power plants, or major cities visually occur only as local anomalies. For Ag in organogenic topsoil the maximum possible input due to diffuse contamination is estimated to be in the 0.02 mg/kg range, about 10% of the median concentration in the soil O horizon. For Hg this value is slightly higher at 0.03 mg/kg. In the soil O horizon Hg concentrations show less variability than in the C horizon. Substantial Hg soil contamination should lead to noticeably increased Hg/Ag ratios.

Identification of the co-existence of low total organic carbon contents and low pH values in agricultural soil in north-central Europe using hot spot analysis based on GEMAS project data.

Total organic carbon (TOC) contents in agricultural soil are presently receiving increased attention, not only because of their relationship to soil fertility, but also due to the sequestration of organic carbon in soil to reduce carbon dioxide emissions. In this research, the spatial patterns of TOC and its relationship with pH at the European scale were studied using hot spot analysis based on the agricultural soil results of the Geochemical Mapping of Agricultural Soil (GEMAS) project. The hot and cold spot maps revealed the overall spatial patterns showing a negative correlation between TOC contents and pH values in European agricultural soil. High TOC contents accompanying low pH values in the north-eastern part of Europe (e.g., Fennoscandia), and low TOC with high pH values in the southern part (e.g., Spain, Italy, Balkan countries). A special feature of co-existence of comparatively low TOC contents and low pH values in north-central Europe was also identified on hot and cold spot analysis maps. It has been found that these patterns are strongly related to the high concentration of SiO2 (quartz) in the coarse-textured glacial sediments in north-central Europe. The hot spot analysis was effective, therefore, in highlighting the spatial patterns of TOC in European agricultural soil and helpful to identify hidden patterns.

Bioavailable 87Sr/86Sr in European soils: A baseline for provenancing studies.

We present 87Sr/86Sr isotope ratios for ~1200 selected soil samples, collected by the GEMAS consortium from grazing (Gr) and agricultural (Ap) soils in Europe with the aim to better understand the strontium isotope distribution in the bioavailable fraction of the top-soil and its potential for provenancing applications. Spatial analysis shows that there is a clear distinction between coastal (<100 km) and non-coastal (>100 km) samples in their variance and that this variance is mirrored in the sodium concentration, suggesting an important but highly variable contribution from seaspray. We present two 87Sr/86Sr maps at 25 km × 25 km scale: one based solely on the measured data using a classical kriging approach and one based on a Random Forest model using complementary GEMAS data to predict the strontium isotope composition at the remaining 3000+ GEMAS sampling locations, including appropriate uncertainty assessment. Using a forensic Bayesian likelihood ratio approach, a tool was developed in R to create provenancing likelihood ratio maps. The maps delineate areas of high and low likelihood and allow investigators to direct their resources to areas of interest. For actual forensic case work either the measured or the modelled data can be used as reference data for the overall distribution of 87Sr/86Sr values in Europe.

Reliability of geochemical analyses: Deja vu all over again.

Today the vast majority of commercial laboratories are accredited. Quality control (QC) results are documented and, upon request, available to the customer. That has led many customers of analytical services to neglect the need for their own, laboratory independent, external QC for large geochemical mapping or monitoring projects. Here, based on recent examples from projects of the Geological Survey of Norway, it is demonstrated how such an external QC procedure should look. Simple graphics are used to visualize QC results. R scripts for producing these graphics are provided. Despite of the laboratories' own internal QC procedures, a number of quality issues like time trends, sample mix-ups, concentration breaks between different batches due to the use of several instruments and excessive rounding of analytical results were detected. Thus, even in these times of accreditation, it is still a necessity to install project-level, laboratory independent, QC procedures in order to produce reliable and comparable datasets.

The large-scale distribution of Cu and Zn in sub- and topsoil: Separating topsoil bioaccumulation and natural matrix effects from diffuse and regional contamination.

A realistic estimate of diffuse contamination requires to recognize and assess the dominant natural and anthropogenic element sources. For eight large-scale geochemical surveys, the relations between geogenic, anthropogenic and biogenic Cu and Zn sources are estimated by comparing the cumulative distribution functions (CDF) of the elements in top- and subsoil using cumulative probability (CP) diagrams. Strong local contamination distorts the high-concentration end of the distribution function considerably in topsoil. In contrast the impact of diffuse contamination can best be recognized at the lower end of the data distribution. Copper and Zn are important plant micronutrients, studying their concentrations in a variety of plant materials and soils along a number of transects demonstrates that both are adjusted to narrow concentration levels in many plant materials. Plants regulating the element concentrations to certain fixed levels will distort the low-concentration end of a topsoil CDF, the bio-adjustment thus limits the accuracy of diffuse contamination estimates. Combining CDF analysis with spatial mapping provides insight into the dominant contamination processes that distort the topsoil CDF relative to the subsoil CDF. For Cu a most likely diffuse contamination signal of 1-2 mg/kg with a maximum of 5 mg/kg is obtained for soils at the European scale. The higher estimate is clearly influenced by bio-adjustment. For Zn diffuse contamination appears to be higher on first glance, about 5-10 mg/kg, but again the lower end of the investigated CDFs is strongly shifted by biosphere adjustment, plants striving to avoid Zn deficiency. The true input through diffuse contamination will thus be considerably lower. Data from projects that sampled minerogenic instead of organogenic topsoil lead to lower estimates for diffuse Zn contamination in the range of <1-5 mg/kg at the continental scale.

Cadmium enrichment in topsoil: Separating diffuse contamination from biosphere-circulation signals.

Eight regional to continental scale datasets providing Cd concentrations in subsoil (C horizon or mineral soil collected at depth) and topsoil are used to compare the statistical distribution of Cd in the two soil layers. Topsoil is invariably enriched in Cd when compared to subsoil. When both horizons are mineral soil the concentration ratio CdTOP/CdSUB is 1.3-2.2. This ratio is substantially larger (6.6-16.5) when mineral subsoil is compared to an organic topsoil O horizon. Data from regional multi-media transects underline that Cd, despite of toxicity, plays an important role in the biosphere, and several plants and a mushroom not only accumulate but also adjust their Cd content. Because organic topsoil is derived from local vegetation residues, its Cd cumulative distribution function (CDF) reflects also Cd accumulation related to local plant diversity. This is a major difference to Pb which is not usually actively taken up by plants, whereby a linear concentration shift between mineral soil and organic soil dominates the CDFs. To estimate the amount of excess Cd due to diffuse contamination, the low-concentration ends of the CDFs from the regional datasets are studied. For two datasets a diffuse Cd contamination below 0.03 mg/kg emerges, a reasonable value when compared to either the median concentration of 0.15 mg/kg Cd in topsoil, or to published Cd fluxes. For the other datasets the apparent diffuse Cd input is between 0.05 and 0.28 mg/kg. In one data set this seems to indicate a true contamination blanket due to several large-scale regional anthropogenic sources at the single country scale. In many surveys, the low end of the subsoil Cd concentration is difficult to assess due to analytical limitations. The results suggest that hitherto neglected natural processes selectively accumulate Cd and substantially change its distribution characteristics in the biosphere and the organic topsoil.

U-Th signatures of agricultural soil at the European continental scale (GEMAS): Distribution, weathering patterns and processes controlling their concentrations.

Agricultural soil (Ap-horizon, 0-20cm) samples were collected in Europe (33 countries, 5.6millionkm2) as part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil-mapping project. The GEMAS survey area includes diverse groups of soil parent materials with varying geological history, a wide range of climate zones, and landscapes. The soil data have been used to provide a general view of U and Th mobility at the continental scale, using aqua regia and MMI® extractions. The U-Th distribution pattern is closely related to the compositional variation of the geological bedrock on which the soil is developed and human impact on the environment has not concealed these genuine geochemical features. Results from both extraction methods (aqua regia and MMI®) used in this study support this general picture. Ternary plots of several soil parameters have been used to evaluate chemical weathering trends. In the aqua regia extraction, some relative Th enrichment-U loss is related to the influence of alkaline and schist bedrocks, due to weathering processes. Whereas U enrichment-Th loss characterizes soils developed on alkaline and mafic bedrock end-members on one hand and calcareous rock, with a concomitant Sc depletion (used as proxy for mafic lithologies), on the other hand. This reflects weathering processes sensu latu, and their role in U retention in related soils. Contrary to that, the large U enrichment relative to Th in the MMI® extraction and the absence of end-member parent material influence explaining the enrichment indicates that lithology is not the cause of such enrichment. Comparison of U and Th to the soil geological parent material evidenced i) higher capability of U to be weathered in soils and higher resistance of Th to weathering processes and its enrichment in soils; and, ii) the MMI® extraction results show a greater affinity of U than Th for the bearing phases like clays and organic matter. The comparison of geological units with U anomalies in agricultural soil at the country scale (France) enables better understanding of U sources in the surficial environment and can be a useful tool in risk assessments.

Geosphere-biosphere circulation of chemical elements in soil and plant systems from a 100 km transect from southern central Norway.

Geochemical element separation is studied in 14 different sample media collected at 41 sites along an approximately 100-km long transect north of Oslo. At each site, soil C and O horizons and 12 plant materials (birch/spruce/cowberry/blueberry leaves/needles and twigs, horsetail, braken fern, pine bark and terrestrial moss) were sampled. The observed concentrations of 29 elements (K, Ca, P, Mg, Mn, S, Fe, Zn, Na, B, Cu, Mo, Co, Al, Ba, Rb, Sr, Ti, Ni, Pb, Cs, Cd, Ce, Sn, La, Tl, Y, Hg, Ag) were used to investigate soil-plant relations, and to evaluate the element differentiation between different plants, or between foliage and twigs of the same plant. In relation to the soil C horizon, the O horizon is strongly enriched (O/C ratio > 5) in Ag, Hg, Cd, Sn, S and Pb. Other elements (B, K, Ca, P, S, Mn) show higher concentrations in the plants than in the substrate represented by the C horizon, and often even higher concentrations than in the soil O horizon. Elements like B, K, Ca, S, Mg, P, Ba, and Cu are well tuned to certain concentration levels in most of the plants. This is demonstrated by their lower interquartile variability in the plants than in the soil. Cross-plots of element concentration, variance, and ratios, supported by linear discrimination analysis, establish that different plants are marked by their individual element composition, which is separable from, and largely independent of the natural substrate variability across the Gjøvik transect. Element allocation to foliage or twigs of the same plants can also be separated and thus dominantly depend on metabolism, physiology, and structure linked to biological functions, and only to a lesser degree on the substrate and environmental background. The results underline the importance of understanding the biological mechanisms of plant-soil interaction in order to correctly quantify anthropogenic impact on soil and plant geochemistry.

GEMAS: CNS concentrations and C/N ratios in European agricultural soil.

A reliable overview of measured concentrations of TC, TN and TS, TOC/TN ratios, and their regional distribution patterns in agricultural soil at the continental scale and based on measured data has been missing - despite much previous work on local and the European scales. Detection and mapping of natural (ambient) background element concentrations and variability in Europe was the focus of this work. While total C and S data had been presented in the GEMAS atlas already, this work delivers more precise (lower limit of determination) and fully quantitative data, and for the first time high-quality TN data. Samples were collected from the uppermost 20cm of ploughed soil (Ap horizon) at 2108 sites with an even sampling density of one site per 2500km2 for one individual land-use class (agricultural) across Europe (33 countries). Laboratory-independent quality control from sampling to analysis guaranteed very good data reliability and accuracy. Total carbon concentrations ranged from 0.37 to 46.3wt% (median: 2.20wt%) and TOC from 0.40 to 46.0wt% (median: 1.80wt%). Total nitrogen ranged from 0.018 to 2.64wt% (median: 0.169wt%) and TS from 0.008 to 9.74wt% (median: 0.034wt%), all with large variations in most countries. The TOC/TN ratios ranged from 1.8 to 252 (median: 10.1), with the largest variation in Spain and the smallest in some eastern European countries. Distinct and repetitive patterns emerge at the European scale, reflecting mostly geogenic and longer-term climatic influence responsible for the spatial distribution of TC, TN and TS. Different processes become visible at the continental scale when examining TC, TN and TS concentrations in agricultural soil Europe-wide. This facilitates large-scale land-use management and allows specific areas (subregional to local) to be identified that may require more detailed research.

Publicly available datasets on thallium (Tl) in the environment-a comment on "Presence of thallium in the environment: sources of contaminations, distribution and monitoring methods" by Bozena Karbowska, Environ Monit Assess (2016) 188:640 (DOI 10.1007/s10661-016-5647-y).

This comment highlights a whole series of datasets on thallium concentrations in the environment that were overlooked in the recent review by Karbowska, Environmental Monitoring and Assessment, 188, 640, 2016 in this journal. Geochemical surveys carried out over the last few decades all over the world at various scales and using different sampling media have reported the concentration of thallium (and dozens more elements) in tens of thousands of samples. These datasets provide a 'real-world' foundation upon which source apportionment investigations can be based, monitoring programs devised and modelling studies designed. Furthermore, this comment also draws attention to two global geochemical mapping initiatives that should be of interest to environmental scientists.

Quantifying Diffuse Contamination: Method and Application to Pb in Soil.

A new method for detecting and quantifying diffuse contamination at the continental to regional scale is based on the analysis of cumulative distribution functions (CDFs). It uses cumulative probability (CP) plots for spatially representative data sets, preferably containing >1000 determinations. Simulations demonstrate how different types of contamination influence elemental CDFs of different sample media. It is found that diffuse contamination is characterized by a distinctive shift of the low-concentration end of the distribution of the studied element in its CP plot. Diffuse contamination can be detected and quantified via either (1) comparing the distribution of the contaminating element to that of an element with a geochemically comparable behavior but no contamination source (e.g., Pb vs Rb), or (2) comparing the top soil distribution of an element to the distribution of the same element in subsoil samples from the same area, taking soil forming processes into consideration. Both procedures are demonstrated for geochemical soil data sets from Europe, Australia, and the U.S.A. Several different data sets from Europe deliver comparable results at different scales. Diffuse Pb contamination in surface soil is estimated to be <0.5 mg/kg for Australia, 1-3 mg/kg for Europe, and 1-2 mg/kg, or at least <5 mg/kg, for the U.S.A. The analysis presented here also allows recognition of local contamination sources and can be used to efficiently monitor diffuse contamination at the continental to regional scale.

Establishing geochemical background variation and threshold values for 59 elements in Australian surface soil.

During the National Geochemical Survey of Australia over 1300 top (0-10cm depth) and bottom (~60-80cm depth) sediment samples (including ~10% field duplicates) were collected from the outlet of 1186 catchments covering 81% of the continent at an average sample density of 1 site/5200km2. The <2mm fraction of these samples was analysed for 59 elements by ICP-MS following an aqua regia digestion. Results are used here to establish the geochemical background variation of these elements, including potentially toxic elements (PTEs), in Australian surface soil. Different methods of obtaining geochemical threshold values, which differentiate between background and those samples with unusually high element concentrations and requiring attention, are presented and compared to Western Australia's 'ecological investigation levels' (EILs) established for 14 PTEs. For Mn and V these EILs are so low that an unrealistically large proportion (~24%) of the sampled sites would need investigation in Australia. For the 12 remaining elements (As, Ba, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Sn and Zn) few sample sites require investigation and as most of these are located far from human activity centres, they potentially suggest either minor local contamination or mineral exploration potential rather than pollution. No major diffuse source of contamination by PTEs affects Australian soil at the continental scale. Of the statistical methods used to establish geochemical threshold values, the most pertinent results come from identifying breaks in cumulative probability distributions, the Tukey inner fence and the 98th percentile. Geochemical threshold values for 59 elements, including emerging 'high-tech' critical elements such as lanthanides, Be, Ga or Ge, for which no EILs currently exist, are presented.

GEMAS: prediction of solid-solution partitioning coefficients (Kd) for cationic metals in soils using mid-infrared diffuse reflectance spectroscopy.

Partial least squares regression (PLSR) models, using mid-infrared (MIR) diffuse reflectance Fourier-transformed (DRIFT) spectra, were used to predict distribution coefficient (Kd) values for selected added soluble metal cations (Ag(+), Co(2+), Cu(2+), Mn(2+), Ni(2+), Pb(2+), Sn(4+), and Zn(2+)) in 4813 soils of the Geochemical Mapping of Agricultural Soils (GEMAS) program. For the development of the PLSR models, approximately 500 representative soils were selected based on the spectra, and Kd values were determined using a single-point soluble metal or radioactive isotope spike. The optimum models, using a combination of MIR-DRIFT spectra and soil pH, resulted in good predictions for log Kd+1 for Co, Mn, Ni, Pb, and Zn (R(2) ≥ 0.83) but poor predictions for Ag, Cu, and Sn (R(2) < 0.50). These models were applied to the prediction of log Kd+1 values in the remaining 4313 unknown soils. The PLSR models provide a rapid and inexpensive tool to assess the mobility and potential availability of selected metallic cations in European soils. Further model development and validation will be needed to enable the prediction of log K(d+1) values in soils worldwide with different soil types and properties not covered in the existing model.

GEMAS: prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy.

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program. These calibration soils represented the major properties of the entire 4813 soils of the GEMAS project. Multiple linear regression (MLR) from soil properties, partial least-squares regression (PLSR) using mid-infrared diffuse reflectance Fourier-transformed (DRIFT) spectra, and models using DRIFT spectra plus analytical pH values (DRIFT + pH), were compared with predicted log K(d + 1) values. Apart from selenate (R(2) = 0.43), the DRIFT + pH calibrations resulted in marginally better models to predict log K(d + 1) values (R(2) = 0.62-0.79), compared with those from PSLR-DRIFT (R(2) = 0.61-0.72) and MLR (R(2) = 0.54-0.79). The DRIFT + pH calibrations were applied to the prediction of log K(d + 1) values in the remaining 4313 soils. An example map of predicted log K(d + 1) values for added soluble MoO4(2-) in soils across Europe is presented. The DRIFT + pH PLSR models provided a rapid and inexpensive tool to assess the risk of mobility and potential availability of boric acid and selected oxoanions in European soils. For these models to be used in the prediction of log K(d + 1) values in soils globally, additional research will be needed to determine if soil variability is accounted on the calibration.

The concept of compositional data analysis in practice--total major element concentrations in agricultural and grazing land soils of Europe.

Applied geochemistry and environmental sciences invariably deal with compositional data. Classically, the original or log-transformed absolute element concentrations are studied. However, compositional data do not vary independently, and a concentration based approach to data analysis can lead to faulty conclusions. For this reason a better statistical approach was introduced in the 1980s, exclusively based on relative information. Because the difference between the two methods should be most pronounced in large-scale, and therefore highly variable, datasets, here a new dataset of agricultural soils, covering all of Europe (5.6 million km(2)) at an average sampling density of 1 site/2500 km(2), is used to demonstrate and compare both approaches. Absolute element concentrations are certainly of interest in a variety of applications and can be provided in tabulations or concentration maps. Maps for the opened data (ratios to other elements) provide more specific additional information. For compositional data XY plots for raw or log-transformed data should only be used with care in an exploratory data analysis (EDA) sense, to detect unusual data behaviour, candidate subgroups of samples, or to compare pre-defined groups of samples. Correlation analysis and the Euclidean distance are not mathematically meaningful concepts for this data type. Element relationships have to be investigated via a stability measure of the (log-)ratios of elements. Logratios are also the key ingredient for an appropriate multivariate analysis of compositional data.

New soil composition data for Europe and Australia: demonstrating comparability, identifying continental-scale processes and learning lessons for global geochemical mapping.

New geochemical data from two continental-scale soil surveys in Europe and Australia are compared. Internal project standards were exchanged to assess comparability of analytical results. The total concentration of 26 oxides/elements (Al2O3, As, Ba, CaO, Ce, Co, Cr, Fe2O3, Ga, K2O, MgO, MnO, Na2O, Nb, Ni, P2O5, Pb, Rb, SiO2, Sr, Th, TiO2, V, Y, Zn, and Zr), Loss On Ignition (LOI) and pH are demonstrated to be comparable. Additionally, directly comparable data for 14 elements in an aqua regia extraction (Ag, As, Bi, Cd, Ce, Co, Cs, Cu, Fe, La, Li, Mn, Mo, and Pb) are provided for both continents. Median soil compositions are close, though generally Australian soils are depleted in all elements with the exception of SiO2 and Zr. This is interpreted to reflect the generally longer and, in places, more intense weathering in Australia. Calculation of the Chemical Index of Alteration (CIA) gives a median value of 72% for Australia compared to 60% for Europe. Element concentrations vary over 3 (and up to 5) orders of magnitude. Several elements (total As and Ni; aqua regia As, Co, Bi, Li, Pb) have a lower element concentration by a factor of 2-3 in the soils of northern Europe compared to southern Europe. The break in concentration coincides with the maximum extent of the last glaciation. The younger soils of northern Europe are more similar to the Australian soils than the older soils from southern Europe. In Australia, the central region with especially high SiO2 concentrations is commonly depleted in many elements. The new data define the natural background variation for two continents on both hemispheres based on real data. Judging from the experience of these two continental surveys, it can be concluded that analytical quality is the key requirement for the success of global geochemical mapping.